docstr: Entering the stream mode enables image stream prediction. Users can predict the images like a stream and save the results to a video.
  
  output_dir: specify the dir to save the results
  visualization: if True, save the results as a video, otherwise not.
  draw_threshold: the threshold for the prediction results
  use_gpu: if True, use gpu to perform the computation, otherwise cpu.
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code: def stream_mode(
      self,
      output_dir="mot_result",
      visualization=True,
      draw_threshold=0.5,
      use_gpu=False,
  ):
      """
      Entering the stream mode enables image stream prediction. Users can predict the images like a stream and save the results to a video.
  
      output_dir: specify the dir to save the results
      visualization: if True, save the results as a video, otherwise not.
      draw_threshold: the threshold for the prediction results
      use_gpu: if True, use gpu to perform the computation, otherwise cpu.
      """
      self.output_dir = output_dir
      self.visualization = visualization
      self.draw_threshold = draw_threshold
      self.use_gpu = use_gpu
  
      cfg = load_config(
          os.path.join(
              self.directory, "config", "jde_darknet53_30e_1088x608.yml"
          )
      )
      check_config(cfg)
  
      place = "gpu:0" if use_gpu else "cpu"
      place = paddle.set_device(place)
  
      paddle.disable_static()
      self.tracker = StreamTracker(cfg, mode="test")
  
      # load weights
      self.tracker.load_weights_jde(self.pretrained_model)
      signal.signal(signal.SIGINT, self.signalhandler)
      return self
  
imports: import argparse
  import glob
  import os
  import signal
  import sys
  import cv2
  import paddle
  from ppdet.core.workspace import load_config
  from ppdet.core.workspace import merge_config
  from ppdet.engine import Tracker
  from ppdet.utils.check import check_config
  from ppdet.utils.check import check_gpu
  from ppdet.utils.check import check_version
  from ppdet.utils.logger import setup_logger
  import paddlehub
  from .tracker import StreamTracker
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.module import runnable
  from paddlehub.module.module import serving
label_desc: Use image node_id 3 for calling the JDETracker_1088x608 obj's underlying member method code with example usage: obj.stream_mode(output_dir, visualization, draw_threshold, use_gpu) and returns: self